Modeling the processes of soil moisture in regulating microbial and carbon-nitrogen cycling

JOURNAL OF HYDROLOGY

卷:585

Article

Wang, Gangsheng^1,2  Huang, Wenjuan^3,4  Zhou, Guoyi⁵  Mayes, Melanie A.^6,7  Zhou, Jizhong^1,2,8,9 

[1] Univ Oklahoma, Inst Environm Genom, Norman, OK 73019 USA

[2] Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA

[3] Chinese Acad Sci, Key Lab Vegetat Restorat & Management Degraded Ec, South China Bot Garden, Guangzhou 510650, Peoples R China

[4] Iowa State Univ, Dept Ecol Evolut & Organismal Biol, Ames, IA 50011 USA

[5] Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Nanjing 210044, Peoples R China

[6] Oak Ridge Natl Lab, Environm Sci Div, POB 2009, Oak Ridge, TN 37831 USA

[7] Oak Ridge Natl Lab, Climate Change Sci Inst, POB 2009, Oak Ridge, TN 37831 USA

[8] Lawrence Berkeley Natl Lab, Earth & Environm Sci, Berkeley, CA 94270 USA

[9] Tsinghua Univ, Sch Environm, State Key Joint Lab Environm Simulat & Pollut Con, Beijing 100084, Peoples R China

关键词: Dynamic data;    Microbial modeling;    Microbial dormancy;    Soil carbon and nitrogen;    Soil microbe;    Soil moisture;   

DOI  :  10.1016/j.jhydrol.2020.124777

来源: Elsevier

【 摘 要 】

Soil carbon (C) and nitrogen (N) cycles and their complex responses to hydro-climatic forcing have gained increasing attention. While the temperature effects have been intensively studied, soil moisture response functions (SMRFs) are not well documented for various microbial and enzymatic processes due to the difficulties in directly measuring and differentiating the moisture effects on various processes. Here we extended our C-only Microbial-ENzyme Decomposition (MEND) model to the C-N coupled MEND model with flexible element stoichiometry. Our model calibration showed good agreement between simulated and observed C:N ratios in soil organic matter and microbial biomass, as well as the ammonium and nitrate concentrations. We show that the selection of SMRFs for specific biogeochemical processes could result in significant differences in model simulated microbial and C-N processes. In particular, it is essential to account for the soil moisture effects on microbial dormancy and resuscitation, as the changes in microbial physiology under favorable or stressful conditions will exert strong controls on soil C and N dynamics. We also advocate the utilization of dynamic (timevariant) data (e.g., litter input, N deposition, soil temperature and moisture), instead of time-invariant data, to drive model simulations and analyses. Dynamic forcing data (particularly dynamic soil moisture) better represent the real-world climate and environmental conditions, which could facilitate more realistic modeling and understanding of soil C and nutrient cycling in a changing world.

【 授权许可】

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